We extract property listings, price histories, energy ratings, and agency portfolios from Casa.it. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Property Listings objects from casa.it. All fields typed and schema-versioned.
"property_id": "c-123456", "title": "Trilocale in vendita a Milano", "price": 450000, "surface_area": 95, "rooms": 3, "energy_class": "A4", "bathrooms": 2
| # | property_id | title | description | price | property_type | surface_area |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Valuation objects from casa.it. All fields typed and schema-versioned.
"property_id": "c-123456", "current_price": 450000, "original_price": 475000, "price_per_sqm": 4736.84, "listing_date": "2023-10-15", "price_dropped": true, "drop_percentage": 5.2
| # | property_id | current_price | original_price | price_per_sqm | currency | listing_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Agency Data objects from casa.it. All fields typed and schema-versioned.
"agency_id": "ag-9876", "agency_name": "Tecnocasa Milano Centro", "city": "Milano", "phone_number": "+39 02 1234567", "active_listings_count": 45, "rating": 4.8
| # | agency_id | agency_name | agency_url | address | city | phone_number |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Property Features objects from casa.it. All fields typed and schema-versioned.
"property_id": "c-123456", "year_built": 2018, "condition": "Excellent / Refurbished", "heating_type": "Central", "elevator": true, "balcony": true, "parking_spaces": 1
| # | property_id | year_built | condition | heating_type | air_conditioning | elevator |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Location & Neighbourhood objects from casa.it. All fields typed and schema-versioned.
"property_id": "c-123456", "region": "Lombardia", "province": "Milano", "municipality": "Milano", "neighbourhood": "Porta Romana", "zip_code": "20122"
| # | property_id | region | province | municipality | neighbourhood | zip_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Casa.it scraper handles the complexities of real estate portals: pagination limits, dynamic map rendering, and coordinate extraction, with Italian residential proxies built in.
Capture price, surface area, room counts, and full descriptions for every property in the target region.
Monitor active listings per agency, time on market, and geographic focus areas.
Track price drops and valuation changes across listing lifecycles with daily diffing.
Extract Energy Performance Certificate (APE) classes and consumption metrics.
Parse latitude and longitude coordinates for precise spatial analysis.
Extract high-resolution image URLs, floor plan links, and virtual tour references.
Detect when properties transition from active to under offer or sold.
Navigate deep search results past the standard 50-page limit using coordinate-based bounding boxes.
Only process records that have updated since the last pipeline run to minimise compute costs.
Brief in. Clean data out.
Provide target municipalities, property types, or agency URLs. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and session management for casa.it.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket or BigQuery dataset on agreed cadence.
Real estate portals actively block automated data collection. Here is how we maintain pipeline stability.
Casa.it caps search results at a fixed number of pages. We bypass this by programmatically subdividing geographic bounding boxes until all results are exposed.
We route requests through Italian residential proxies to avoid IP bans and geoblocking heuristics.
Property coordinates are often loaded via background API calls. We intercept the XHR traffic rather than parsing the DOM.
DOM structures change between private listings and agency listings. We use fallback chains to normalise the output schema.
We maintain a hash index to identify when properties are delisted, providing accurate active-inventory metrics.
Feed current market prices, surface areas, and location data into machine learning models for property valuation.
Real estate networks monitor rival agency portfolios, listing volumes, and geographic market share.
Correlate sale prices with rental yields in specific neighbourhoods to identify high-ROI investment targets.
Measure average time on market and price-drop frequencies to gauge regional housing demand.
Analyse the distribution of energy classes (A4 to G) across different provinces and building ages.
Provide structured housing data to municipal planners and demographic researchers.
"Casa.it holds the definitive record of Italian property transactions, but extracting structured data requires bypassing strict pagination limits and anti-bot systems."
Most teams underestimate the complexity of real estate scraping. Reliable Casa.it extraction requires Italian residential proxies, coordinate-based search subdivision to bypass pagination limits, and daily schema maintenance. DataFlirt absorbs that operational overhead so your analysts can focus on market trends, not broken web scrapers.
Everything supported by our casa.it scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and retry logic. Playwright executes JavaScript for map hydration and dynamic content.
We maintain pools of Italian residential ISP proxies. Rotation happens per-request to prevent IP reputation degradation.
Pipelines run on AWS ECS. Airflow handles scheduling and dependency management. State is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About casa.it scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available real estate listings is generally permissible under EU law, provided it does not extract personal data protected by GDPR. We target public property and agency data. Clients must consult legal counsel for specific commercial use cases.
Casa.it caps search results to prevent mass scraping. We bypass this by programmatically subdividing geographic bounding boxes into smaller grids until every region returns fewer than the maximum allowed results, ensuring 100% market coverage.
We monitor active listings and flag them when they are removed from the portal or marked as under offer, providing a reliable proxy for transaction volume and time-on-market metrics.
Yes. We intercept the backend API calls that populate the map view, allowing us to extract precise latitude and longitude coordinates even when the frontend obscures them.
We support daily or weekly pipeline cadences. For high-priority regional markets, we can configure hourly change-detection runs to capture new listings within minutes of publication.
We typically start at a defined regional scope (e.g., all listings in Lombardy) with weekly delivery. Pricing scales based on the total volume of listings monitored and the update frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily feed of Milan property prices or a complete historical dump of Italian agency portfolios, we build and operate the infrastructure. Tell us your requirements.
